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optimize _get_min_width function (alternative solution) #5

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optimize _get_min_width function (alternative solution) #5

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48 changes: 18 additions & 30 deletions src/reference_path.py
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Original file line number Diff line number Diff line change
Expand Up @@ -227,7 +227,8 @@ def _compute_width(self, max_width):
t_x, t_y = self.map.w2m(wp.x + max_width * np.cos(angle), wp.y
+ max_width * np.sin(angle))
# Compute distance to orthogonal cell on path border
b_value, b_cell = self._get_min_width(wp, t_x, t_y, max_width)
b_value, b_cell = self._get_min_width(wp, t_x, t_y)

# Add information to list for current waypoint
width_info.append(b_value)
width_info.append(b_cell)
Expand All @@ -240,49 +241,36 @@ def _compute_width(self, max_width):
wp.static_border_cells = (width_info[1], width_info[3])
wp.dynamic_border_cells = (width_info[1], width_info[3])

def _get_min_width(self, wp, t_x, t_y, max_width):
def _get_min_width(self, wp, t_x, t_y):
"""
Compute the minimum distance between the current waypoint and the
orthogonal cell on the border of the path
:param wp: current waypoint
:param t_x: x coordinate of border cell in map coordinates
:param t_y: y coordinate of border cell in map coordinates
:param max_width: maximum path width in m
:return: min_width to border and corresponding cell
"""

# Get neighboring cells of orthogonal cell (account for
# Get pixel coordinates of waypoint
wp_x, wp_y = self.map.w2m(wp.x, wp.y)

# Repeat for neighboring cells of orthogonal cell (account for
# discretization inaccuracy)
tn_x, tn_y = [], []
path_x = np.array([]) # store border cells if path goes through them
path_y = np.array([])
for i in range(-1, 2, 1):
for j in range(-1, 2, 1):
tn_x.append(t_x+i)
tn_y.append(t_y+j)
x_list, y_list, _ = line_aa(wp_x, wp_y, t_x + i, t_y + j)

# Get pixel coordinates of waypoint
wp_x, wp_y = self.map.w2m(wp.x, wp.y)
occupied = (self.map.data[y_list, x_list] == 0)
path_x = np.append(path_x, x_list[occupied])
path_y = np.append(path_y, y_list[occupied])

# Get Bresenham paths to all possible cells
paths = []
for t_x, t_y in zip(tn_x, tn_y):
x_list, y_list, _ = line_aa(wp_x, wp_y, t_x, t_y)
paths.append(zip(x_list, y_list))

# Compute minimum distance to border cell
min_width = max_width
# map inspected cell to world coordinates
min_cell = self.map.m2w(t_x, t_y)
for path in paths:
for cell in path:
t_x, t_y = cell[0], cell[1]
# If path goes through occupied cell
if self.map.data[t_y, t_x] == 0:
# Get world coordinates
c_x, c_y = self.map.m2w(t_x, t_y)
cell_dist = np.sqrt((wp.x - c_x) ** 2 + (wp.y - c_y) ** 2)
if cell_dist < min_width:
min_width = cell_dist
min_cell = (c_x, c_y)
c_x, c_y = self.map.m2w(path_x, path_y)
widths = np.hypot(wp.x - c_x, wp.y - c_y)
min_index = np.argmin(widths)
min_width = widths[min_index]
min_cell = (c_x[min_index], c_y[min_index])

return min_width, min_cell

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